System and methods for assessing heart function

ABSTRACT

Systems and methods can be used to provide an indication of heart function, such as an indication of mechanical function or hemodynamics of the heart, based on electrical data. For example, a method for assessing a function of the heart can include determining a time-based electrical characteristic for a plurality of points distributed across a spatial region of the heart. The plurality of points can be grouped into at least two subsets of points based on at least one of a spatial location for the plurality of points or the time-based electrical characteristics for the plurality of points. An indication of synchrony for the heart can be quantified based on relative analysis of the determined time-based electrical characteristic for each of the at least two subsets of points.

RELATED APPLICATION

This application claims the benefit of U.S. provisional patentapplication No. 61/409,714 filed Nov. 3, 2010, and entitled SYSTEM ANDMETHODS FOR ASSESSING HEART FUNCTION, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

This disclosure relates to systems and methods for assessing heartfunction.

BACKGROUND

The normal electrical conduction of the heart allows electricalpropagation to stimulate the myocardium. Time ordered stimulation of themyocardium allows efficient contraction of all four chambers of theheart, thereby allowing selective blood flow through both the lungs andsystemic circulation. The ordered stimulation can become de-synchronizedand thereby adversely affect the mechanical function of the heart.

Cardiac resynchronization therapy (CRT) is a method of improving themechanical function of the heart using electrical therapy (e.g., pacingboth the right and left ventricles). Various techniques are utilized todetermine a pacing site as well as to determine pacing parameters.Current mechanical and electrical measures tend to be qualitative andare highly operator dependent due to the complex nature of ventricularactivation and the lack of quantitative comparisons between electricalactivation and mechanical function.

SUMMARY

This disclosure relates to systems and methods for assessing heartfunction, such as based on sensed electrical activity.

As an example, a method for assessing a function of the heart can beprovided. The method can include determining a time-based electricalcharacteristic for a plurality of points distributed across a spatialregion of the heart. The plurality of points can be grouped into atleast two subsets of points based on at least one of a spatial locationfor the plurality of points or the time-based electrical characteristicsfor the plurality of points. An indication of synchrony for the heartcan be quantified based on relative analysis of the determinedtime-based electrical characteristic for the at least two subsets ofpoints. The method can be embodied as instructions stored in a machinereadable medium that can be also be executed by a processor.

As another example, a system can include memory to store data andmachine-executable instructions. The stored data can electrical datarepresenting electrical signals for a plurality of points spatiallydistributed across a cardiac envelope over a period of time. A processorcan access the memory and execute the instructions. When suchinstructions are executed, they cause the processor to quantify anindication of synchrony for a patient's heart based on analysis of afirst set of the electrical data associated with a first subset of theplurality of points relative to a second set of set of the electricaldata associated with a second subset of the plurality of points.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example of a system that can be implemented toascertain an indication of heart function.

FIG. 2 depicts an example of a calculator that that can be implementedto compute a first index indicative of heart function.

FIG. 3 depicts part of a heart demonstrating an example of segmentingthe heart into regions.

FIG. 4 depicts an example of a calculator that that can be implementedto compute a second index indicative of heart function.

FIG. 5 depicts examples of histogram data that can be utilized in asystem or method.

FIGS. 6A and 6B depict examples of maps that can be generated fromelectrocardiographic mapping for use in ascertaining an indication ofheart function.

FIG. 7 depicts example of a system that can be implemented to ascertainan indication of heart function to facilitate delivery of a therapy.

FIGS. 8A and 8B depict examples of electrocardiographic maps for abaseline patient condition.

FIGS. 9A and 9B depict examples of electrocardiographic mapsdemonstrating a response to delivery of a therapy for the same patientas in FIGS. 8A and 8B.

FIGS. 10A and 10B depict examples of electrocardiographic maps for abaseline patient condition.

FIGS. 11A and 11B depict examples of electrocardiographic mapsdemonstrating a patient response to delivery of a therapy for the samepatient as FIGS. 10A and 10B.

FIGS. 12, 13 and 14 depict examples of electrocardiographic mapsdemonstrating patient responses for delivery of therapy at differentlocations and with different therapy parameters.

FIG. 15 is a flow diagram illustrating an example of a method todetermine a location for delivery of a therapy.

FIG. 16 is a flow diagram illustrating an example of a method todetermine parameters for delivery of a therapy.

FIG. 17 depicts an example computing environment that can be used toperform methods according to an embodiment of the invention.

DETAILED DESCRIPTION

This disclosure relates to systems and methods for assessing thefunction of the heart. The systems and methods can be employed toprovide a quantitative assessment of heart function (e.g., synchrony)that is computed based on electrical information for one or more regionsof the heart.

As an example, the systems and methods can be utilized to evaluate afunction of the heart based on electrical activity distributed acrossone or more spatial regions of the heart. The regions can includesegmented regions (also referred to herein as segments) within one ormore chambers of the heart. The evaluation further can includecomparative or correlative statistics for the electrical activity amongmultiple heart chambers, such as may include the left and right chambers(e.g., ventricles) of the heart.

As another example, the quantitative analysis can be computed to outputone or more indices that quantify activation time heterogeneity and/orrepolarization time heterogeneity. For instance, one or more indices canbe computed to include one or more of a Global InterventricularSynchrony (GIS) Index, a Segmental Synchrony Index (SIS), anIntraventricular Conduction Index (ICI) or a late activation (LAI)index. Each index can be calculated based solely on measured electricalactivity (e.g., without the need for mechanical data for the heart). Forinstance, the electrical activity can be measured via non-invasivemethods. Systems and methods can generate graphical outputs based onthese or other indications of synchrony to facilitate the assessment ofcardiac function.

The quantitative assessment of synchrony can also be utilized tofacilitate delivery of a therapy. For example, an indication of cardiacsynchrony can be computed intraoperatively and used to guideadministration of therapy to the patient (e.g., providing closed loopfeedback during delivery of therapy). The guidance can include spatialguidance to locate one or more sites to which the therapy may beapplied. Additionally or alternatively, the guidance can provideinformation to set and/or provide automated control for therapyparameters (e.g., a quantity and duration of a given therapy as well asa delay time between delivery of consecutive therapies).

As one example, the index can be computed used to guide CRT therapy,such as taking into account both the delivery method (the accessiblelocations where a pacing lead can be anchored) and providing informationabout the health of the substrate. For determining the treatmentparameters (e.g., location as well as stimulation parameters), eachtreatment parameter can be varied for a given patient and the indexcomputed for a plurality of different treatment parameters. This processcan be repeated and the results evaluated to ascertain treatmentparameters to achieve desired therapeutic effect.

FIG. 1 depicts an example of a system 10 for assessing cardiac functionof a patient. The system 10 can be implemented in a standalone computer,a workstation, an application specific machine, or in a networkenvironment in which one or more of the modules or data can residelocally or remotely relative to where a user interacts with the system10.

The system 10 employs patient data 12 for one or more patient, such ascan be stored in an associated memory device (e.g., locally orremotely). The patient data 12 can include electrical data 14 thatrepresents electrical information for a plurality of points, each ofwhich is indexed or otherwise programmatically associated with (e.g.,linked to) an anatomical geometry of the patient. The patient data 12can also include geometry data 16, such as can be embodied as a geometrymodel for a three-dimensional region of anatomy. The model can be ageneric model, which can be tailored for a given patient based onmeasurements and/or imaging data for the patient. Alternatively, thegeometry data can be a patient-specific model that is generated based onimaging data for the patient. In one example, the geometry data 16 cancorrespond to a surface of model of a given patient's entire organ, suchas the heart, which can be graphically rendered as a two- orthree-dimensional representation.

The patient electrical data 14 can be raw data, such as has beencollected from an electrophysiology mapping catheter or other means thatcan be utilized to acquire electrophysiology data for a selected regionof a patient (e.g., of an organ, such as the heart). Additionally oralternatively, the electrical data 14 can correspond to processed data,such as can be computed from raw data to provide electrophysiologyinformation for the selected region of the patient (e.g., a cardiacenvelope for the heart).

By way of example, non-invasive electrophysiological mapping (e.g.,electrocardiographic (EC) mapping for the heart) can be performed on abody surface of the patient to generate the electrical data 14. Thistechnique can generate electrophysiological data by combining bodysurface electrical measurements with patient geometry informationthrough an inverse method programmed to reconstruct the electricalactivity for a predetermined surface region of the patient's heart.Thus, the results of the inverse method can provide the correspondingelectrical data 14 that is registered with the patient geometry data 16.Thus, the electrical data 14 can represent reconstructed electricalsignals (e.g., time-based electrical potentials) for each of theplurality of points on a cardiac envelope concurrently as a function oftime, such as an epicardial surface, endocardial surface or otherenvelope. Examples of inverse algorithms that can be utilized in thesystem 10 are disclosed in U.S. Pat. Nos. 7,983,743 and 6,772,004, whichare incorporated herein by reference.

In another embodiment, a contact or non-contact electrophysiologycatheter can be placed in a patient's heart and collectelectrophysiology data at a plurality of spatial locations over time,such as during a number of one or more cardiac intervals. Such data canbe spatially and temporarily aggregated in conjunction with image datafor the patient's heart to provide the electrical data 14 forcorresponding regions of the patient's heart. Alternatively, otherdevices (e.g., catheters or patches) can be placed on or near apatient's heart, endocardially and/or epicardially, such as during openchest and minimally invasive procedures, to record electrical activitydata, which can be mapped to a representation of the patient's heart toprovide similar corresponding electrical data 14.

Those skilled in the art will understand and appreciate that the system10 is equally applicable to patient electrical data 14 that can begathered and/or derived by any of these or other approaches, which maybe invasive or non-invasive. Additionally, it will be understood andappreciated that the electrical data 14 can be provided in any form andconverted into an appropriate form for processing in the system 10.

As mentioned above, the system 10 also employs geometry data 16, such ascan represent a predetermined surface region of an anatomical structure,which can be a generic structure or be specific for a given patient. Forexample, the geometry data 16 can correspond to a patient-specificrepresentation of a surface of an organ or other structure to which thepatient electroanatomical data has been registered. For instance, thegeometry data 16 may include a graphical representation of a region ofthe patient's organ, such as can be generated by appropriate imageprocessing of image data acquired for the patient. Such image processingcan include extraction and segmentation of an organ from a digital imageset. The segmented image data thus can be converted into atwo-dimensional or three-dimensional graphical representation of asurface region of the patient's organ. Alternatively, the patientgeometry data 16 can correspond to a mathematical model, such as can beconstructed based on image data for the patient's organ. Appropriateanatomical or other landmarks can be associated with the organrepresented by the anatomical data for the organ to facilitatesubsequent processing and visualization in the system 10.

As mentioned above, the electrical data 14 can be registered into acommon coordinate system with the patient geometry data 16. Forinstance, the electrical data 14 can be stored in a data structure ofrows (corresponding to different anatomical points) and columns(corresponding to samples) in which the rows of data have the same indexas (or are registered to) respective points residing on patient geometrydata 16. This registration or indexed relationship between theelectrical data 14 and the geometry data 16 is indicated by a dashedline at 18. In one embodiment, the samples in each of the columns canrepresent simultaneous information across the entire surface region(e.g., the heart) of the patient.

The geometry data 16 can be generated from image data that is acquiredusing nearly any imaging modality. Examples of imaging modalitiesinclude ultrasound, computed tomography (CT), 3D Rotational angiography(3DRA), magnetic resonance imaging (MRI), x-ray, positron emissiontomography (PET), and the like. Such imaging can be performed separately(e.g., before or after the measurements) utilized to generate theelectrical data 14. Alternatively, imaging may be performed concurrentlywith recording the electrical activity that is utilized to generate thepatient electrical data 14.

It will be understood and appreciated by those skilled in the art thatthe system 10 is equally applicable to employ anatomical data that maybe acquired by any one of these or other imaging modalities. The type ofimaging modality can vary according to the purpose or purposes of thedata 16. For example, CT provides an effective modality for use inperforming the inverse method in conjunction with body surfaceelectrodes used in performing electrical measurements for generating theelectrical data 14 as EC mapping data. MR imaging is useful foridentifying areas of scar in the heart, such as for identifying areas(e.g., scar areas) to be excluded from subsequent processing andevaluation, as disclosed herein. Thus, one or more image sets can beacquired by one or more imaging modalities, each of which can beco-registered with and collectively stored as the patient geometry data16.

Alternatively or additionally, the geometry data 16 can correspond to ageneric or custom representation of an organ, which may not be thepatient's own organ. In such a case, the electrical data 14 can bemapped (via registration 18) to the representation of the organaccording to identified anatomical landmarks. A manual, semi-automaticor automatic registration process can be employed in order to registerthe anatomical model with the signal acquisition system, if any.

It further will be understood and appreciated that depending upon theformat and type of input data appropriate formatting and conversion to acorresponding type of representation can be implemented by the system10. For instance, the patient data 12 can include electrical data thatis provided to the system 10 in a known format or be converted to astandard format for processing by the system. Thus, the patient data 12can include an aggregate set of electrical data for the patient.

An analysis system 20 is programmed to compute an assessment of heartfunction. The analysis system 20 can be implemented ascomputer-executable instructions implemented on a processor runningremotely or locally on a computer where the patient data 12 is stored. Auser interface 22 can be utilized to activate or otherwise interact withthe analysis system 20 such as for calculating an indication ofsynchrony, such as described herein. As used herein, the indication ofsynchrony can be employed to provide a quantitative measure of synchronyfor the heart or a measure of dyssynchrony for the heart or acombination of synchrony and dyssynchrony. For purposes of consistencyherein, however, such measures are referred to herein as relating tosynchrony.

The user interface 22 can provide a graphical and/or other interfacethat allows a user to provide a user input for initiating the process.The user interface 22 can also be utilized to set and establish datapaths and variables employed by the analysis system 20. The userinterface 22 can also be utilized to configure the computationsperformed by the analysis system 20 and/or one or more output devices 30that can be provided. For instance, the user interface 22 can configurethe types of methods and parameters utilized in forming the analysisbased on the patient data 12.

The analysis system 20 can also include an exclusion component 24 thatidentifies areas of patient geometry that are to be excluded. Theidentified areas can be excluded from analysis (e.g., by making allelectrical activity zero for such excluded points) or the identifiedareas can be removed from the results provided by the analysis system20. For example, the exclusion component 24 can be employed to identifyone or more areas that do not contribute to mechanical function as wellas areas that will not respond to stimulation from electrodes. Theexclusion component 24 can be programmed as code that is executed toautomatically identify areas to be excluded. Alternatively oradditionally, the exclusion component 24 can set the one or more areasto be excluded in response to user inputs provided via the userinterface 22. The identification of areas to be excluded can beperformed based on geometry data 16, patient electrical data 14 as wellas based on a combination thereof.

For example, the geometry data 16 can include MRI data for the patient'sheart, which can be utilized to identify scar areas. The scar areas canbe co-registered with the electrical data 14, and thereby be utilized toexclude such regions from subsequent analysis, such that points in suchexcluded regions are not utilized by the analysis system 20 inquantifying synchrony. Those skilled in the art will understand andappreciate other types of imaging technology or other means that can beutilized to identify such scar areas.

Additionally or alternatively, the exclusion component 24 can identifyelectrical properties of areas corresponding to scarring or otherregions that may be non responsive to electrical stimulation. Forexample, the exclusion component 24 may access a subset of methods forcomputing or otherwise identifying areas of low-voltage electrograms,areas of fractionated electrogram morphology as well as areas of low orerratic conduction rates (dV/dT). The excluded areas can be populated tothe electrical data 14 or otherwise utilized in the process forselectively excluding those areas that have been identified forexclusion from analysis.

The analysis system 20 also includes a time calculator 26 that isprogrammed to compute a temporal characteristic for each of a pluralityof points on the cardiac envelope for which the electrical activity hasbeen determined. For instance, the temporal characteristic can becomputed for a selected beat (e.g., a sinus beat) or an interval thatincludes more than one beat. The beat or interval can be selected by theuser interface 22 by manual user input. Alternatively or additionallythe analysis system 20 can automatically identify and select a beat forwhich temporal characteristic will be calculated by the time calculator26. The temporal characteristic thus can be computed for each of theplurality (e.g., thousands) of points on the surface of the heart forthe same heart beat or other associated time interval. Additionally, theselected interval can be applied to filter the electrical data 14 suchthat electroanatomic data is provided for the selected beat.

As demonstrated in the example of FIG. 1, the time calculator 26 caninclude an activation time calculation component 27 programmed tocompute an activation time for the plurality of points on the cardiacenvelope. Additionally or alternatively, the time calculator 26 caninclude a repolarization time calculation component 29 programmed tocompute a repolarization time for the plurality of points on the cardiacenvelope.

The analysis system 20 also includes a synchrony calculator 28 that isprogrammed to quantify an indication of synchrony based on the one ormore temporal characteristics computed by the time calculator 26 foreach of the non-excluded areas of the heart. That is, the synchronycalculator 28 may not compute the indication of synchrony for points onthe cardiac envelope determined to reside in excluded areas.Alternatively, depending upon application requirements, indexes can becomputed for all points on the cardiac envelope and those indexescomputed for excluded areas can be excluded from results and evaluation.In some cases, no areas will be excluded. Those areas of exclusionidentified via the exclusion component 24 further can be visualized onan output device 30 such as in a two-dimensional or three-dimensionalrepresentation of the patient's heart.

By way of further example, the synchrony calculator 28 can calculate oneor more index such as including a global synchrony index (GSI), anintraventricular conduction index (ICI) or a segmental synchrony index(SSI), a late activation index, such as according to the methodsdisclosed herein. The synchrony calculator 28 computes an indication ofsynchrony 32 that can be provided to the output device 30 for providinga visualized assessment of a patient's heart function. As describedherein, the index 32 can provide an assessment of heart electricalfunction, heart mechanical function, hemodynamic performance or anycombination thereof.

As one example, the synchrony calculator 28 computes a quantitativemeasure of electrical synchrony as a global synchrony index (GSI). Asone example, the global synchrony index provides a measure of synchronybased upon statistical analysis of activation times for the leftventricle relative to the right ventricle of the patient's heart. Forexample, the synchrony calculator 28 can compute the GSI by computingthe mean and standard deviation of activation times for each ventricle.The GSI index thus corresponds to the difference between the meanactivation times for the left and right ventricle as well as thestandard deviation between the right and left ventricles. As an example,the GSI for the mean and standard deviation calculations can be computedas follows:

GSI_(M)=mean (RV activation times)−mean (LV activation times)

GSI_(SD)=RV standard deviation−LV standard deviation

where the designation RV and LV can mean whole chamber or a selectedpart of the chamber (e.g., such as the free wall).

This GSI can be utilized for determining location and stimulationparameters for CRT. For determining an optimal lead location, theanalysis system 20 can repeat GSI computations for paced beats atdifferent stimulation parameters and different locations. The locationscan further take into account that the delivery of method and the healthof the substrate at which the patient is being applied. A desired sitecan be the site determined to have lowest GSI_(M) index, the lowestGSI_(SD) index or having the lowest combination of indices. Treatmentparameters for CRT can be determined in a similar manner in whichparameters at one or more locations can be adjusted and correspondingGSI data computed. Corresponding parameters can be selected based upontheir evaluations comparing respective GSI indices computed for each setof parameters.

FIG. 2 depicts an example of another index calculation method 50 thatcan be utilized to compute an index that is referred to herein as anintraventricular conduction index (ICI). The index calculation method 50provides the index as index data 52. The index calculation method 50computes the index data based on map data 54, such as activation and/orrepolarization data disclosed herein with respect to FIG. 1. The ICIindex provides a quantitative measure of electrical synchrony relativeto established normal synchrony for each of a plurality of differentsegments determined for the heart.

The index calculation method 50 can employ empirical conduction data 62.The conduction data 62 can include activation and/or repolarizationtimes derived based on clinical or other forms of investigation for apatient population known to have normal conduction patterns. As anexample, the empirical conduction data 62 can be represented as a normalsegmental index associated with the plurality of patients that form apatient population. The patient population further may be arranged orotherwise sortable according to patient health parameters, ageparameters, height or other criteria that can be utilized to generatecustomized relevant patient populations corresponding to a normal classof people consistent with the particular attributes of a given patientfor which the index calculation method 50 is being performed. Theselection of the conduction data can be automated based on attributesentered for the given patient or the conduction can be manually selectedfor a given patient.

In the example of FIG. 2, the index calculation method 50 includes asegment divider 56 that is programmed to divide right and left portions(e.g., ventricles) of the heart into a respective plurality of Nsegments, where N is a positive integer denoting a number of segments(e.g., anatomical regions) into which each ventricle is divided.Examples of the segments for each ventricle can include, for example theapex region, outflow tract, or the like.

FIG. 3 depicts an example of a graphical representation of the heart 70demonstrating an approach where the left ventricle is dividedanatomically into a plurality (e.g., seven) of segments. Those skilledin the art will understand and appreciate various types of segments intowhich each ventricle can be divided, which can correspond to solelyanatomical regions, such as shown in the example of FIG. 3.Alternatively, different chambers of the heart, including theventricles, can be divided into segments according to an expectedcontribution to hemodynamic performance, or mechanical function. As yetanother alternative, the heart can be geometrically divided intosegments that can be of equal size or the sizes of such segments can bedifferent. The different segments of the heart can correspond tocontiguous anatomical regions or a given segment may include anon-contiguous set of points distributed across the heart.

In one embodiment each of the segments of the heart can be selectedaccording to an expected contribution to hemodynamic function for eachof the respective anatomical regions of the corresponding ventricles. Inthis way certain segments of each ventricle that contributecommensurately to hemodynamic and mechanical function of the heart canbe grouped together into a given segment. Corresponding EC mapping data(e.g., time-indexed reconstructed electrical activity data) for pointsresiding within each region can thus be grouped together (e.g., tags orindices) for each respective region for use in performing the indexcalculation method 50.

The index calculation method 50 also includes a segmental indexcalculator 58 that is programmed to compute one or more segmentalindices for each of the N segments into which the right and leftventricles (or other anatomical portions have been divided (e.g., by thesegment divider 56). For instance, the segmental index calculator 58 cancompute one or more segmental indices based on evaluation of activationmap data that has computed and aggregated into the respective N segmentsfor each ventricle for a given beat. The indices can be calculated fromstatistical evaluation of time-based electrical activity data (e.g.,corresponding to activation time and/or repolarization times) for pointswithin each segment. For the example of activation time data, the indexcalculator 58 can compute the segmental index to include a meanactivation time for each segment as well as a standard deviation foreach respective segment. The corresponding segmental indices can bestored in memory.

As mentioned above, the empirical conduction data 62 for each of the Nsegments can also be stored in memory for use in computing the ICI. Thenormal conduction delays can be stored in memory for each of the Nsegments based upon corresponding statistical analysis for respectivesegments for a normal population of patients. For instance, theempirical conduction data 62 can provide a statistical representationfor a normal patient population, such as the mean activation time andstandard deviation of activation time for each of the N segments. Eachof the N values of the conduction data can be linked or otherwiseprogrammatically associated with each of the values computed for the Nregions by the segmental index calculator 58.

The intraventricular conduction index calculator 50 is programmed tocompute the ICI index to represent contributions from each of the Nsegments of the left and right ventricles as a function of the normalconduction delays and the corresponding segmental indexes computed bythe segmental index calculator for each of the N segments. As oneexample, the ICI indices may be computed as follows:

ICI_(m)=ICI_(mLV)−ICI_(mRV)=[sum ABS(SI(n)_(m) −N(n)_(m))

for all segments n in

LV]−[sum ABS(SI(n)_(m) −N(n)_(m))

for all segments n in RV]

ICI_(sdLV)=sum ABS(SI(n)_(sd) −N(n)_(sd))

for all segments n in LV

ICI_(sdRV)=sum ABS(SI(n)_(sd) −N(n)_(sd))

for all segments n in RV

ICI_(sd)=ICI_(sdLV)=ICI_(sdRV)

The intraventricular conduction index calculator 50 in turn generates acorresponding ICI index, including one or any combination of the ICW,ICI_(sdLV), ICI_(sdRV), and ICI_(SD). The corresponding index or indicescan be stored as index data 52 for the interval for which the activationtime corresponds. Corresponding index data 52 can be computed for aplurality of different beats and patient conditions.

As one example, the index data 52 can be computed for a variety ofdifferent pacing lead/electrode locations to identify which location canhelp improve synchrony. The calculations and locations can take intoaccount both delivery method and the health of the substrate for a givenlocation. A desired therapy site thus can be determined based upon anevaluation or comparison of the respective ICI indices computed for eachof a plurality of locations. For example, the lowest ICI_(M) index, thelowest ICI_(SD) index or a combination of respective indices can beutilized to determine the desired pacing site or lead location.Similarly, the ICI indices can be computed for determining optimaltreatment parameters. For instance, ICI indices can be computed for aplurality of different treatment parameters (e.g., for programming a CRTdevice) and the parameters that minimize the ICI index can be utilizedto determine an optimal or desired set of treatment parameters.

As another example, a patient's candidacy for cardiac therapy can beevaluated based on the index data 52. For instance, a level of apatient's dyssynchrony can be determined based on a dispersion ofactivation, such as represented in one or more of the ICI_(sdLV),ICI_(sdRV), and ICI_(SD) indices. Thus, the indices can be comparedrelative to corresponding thresholds to qualify a patient as a candidatefor cardiac therapy, such as including CRT.

FIG. 4 depicts an example of another index calculation method 100 thatcan be utilized to compute index data 104, which is referred to in thisexample as including a segmental synchrony index (SSI). The SSI indexprovides an assessment of mechanical synchrony based on electricalmeasurements. The index calculation method 100 can computes the SSIbased on electrocardiographic map data 106, such as can be determinedfrom measured electrical activity as shown and described herein. The mapdata 106 can represent the activation time and/or repolarization time(or other time-based electrical characteristic) for each of a pluralityof points on a cardiac envelope over one or more beats.

In the example of FIG. 4, the index calculation method 100 includes asegment divider 108 that is programmed to divide the anatomical regionsof the heart into N segments, such as described with respect to FIGS. 2and 3. The time based electrical characteristics represented by the mapdata can be classified and processed according to which segment itbelongs. There can be any number of N regions, which may be establishedaccording to known anatomical regions (e.g., the apex, outflow tract andthe like). The regions can represent contiguous or non-contiguousanatomical areas of the heart.

The index calculation method 100 also includes a segmental indexcalculation 110 that is programmed to calculate a statistical assessmentfor each of the N segments based on the map data for points on the heartresiding in each of the respective segments. For instance, the segmentalindex calculator 110 can calculate a mean and standard deviation of thetime-based electrical characteristics (e.g., activation time and/orrepolarization time) for each of the plurality of points (in the mapdata 106) within each of the N region for each ventricle. For theexample of activation time as the time-based electrical characteristic,the SI for each segment N can be determined, as follows:

SI(N)_(M)=mean activation time in segment N

Similarly, a segmental dispersion of intraventricular activation can bedetermined for each of the LV and RV, as follows:

SI(N)_(SD) _(—) _(LV)=standard deviation for each segments N in LV

SI(N)_(SD) _(—) _(RV)=standard deviation for each segment N in RV

The above calculations for the SSI indices can be computed for each ofthe respective N segments in the left and right ventricles. Thesegmental dispersion further can be employed to identify a segmenthaving an increased dispersion relative to other segments.

The SSI can provide an assessment of mechanical synchrony based onelectrical measurements by weighting each of a plurality of N segmentsin each ventricle according to its contribution to mechanical heartfunction and/or hemodynamic performance. Thus, the index calculationmethod 100 employs segment weighting function 112. The weightingfunction 112 can be represented as SI(n)_(W), which provides a valueestimating the relative contribution that each given segment N makes tomechanical function and/or hemodynamic performance. As an example, theweighting function SI(n)_(W) for each of the N segments can becalculated for each anatomical region from wall motion imaging (e.g.,CT, MRI, fluoroscopy, 2-D or 3-D echocardiograms, or the like). Thecorresponding weight function 112 can thus be determined and stored inmemory associated with each of the N segments of the heart.

The index calculation method 100 also includes a segmental synchronyindex calculator 114 that is programmed to compute the SSI index foreach of the N segments. For example, a corresponding SSI can be computedfor the left ventricle of a given segment and for the right ventricle ofthe corresponding segment and the corresponding difference between therespective segments of each ventricle computed for each of thecorresponding segments. The respective results for each segment can besummed together to provide an indication of the SSI for a patient'sheart. For instance, the SSI computed for a given one of the N segmentscan be multiplied by the corresponding weight for such segment, asprovided by the segment weighting function 112. This can be performedfor each of the N segments. The SSI can be computed as the mean andstandard deviation. For example, the SSI can be calculated as follows:

SSI_(M)=SSI_(MLV)−SSI_(MRV)=[sum (SI(n)_(M)*SI(n)_(W)),

for all segments n in

LV]−[sum (SI(n)_(M)*SI(n)_(W)),

for all segments n in RV]

SSI_(SDLV)=sum (SI(n)_(SD)*SI(n)_(W)),

for all segments n in LV

SSI_(SDRV)=sum (SI(n)_(SD)*SI(n)_(W)),

for all segments n in RV

SSI_(SD)=SSI_(SDLV)+SSI_(SDRV)

for all segments n in whole heart

The index calculation method in turn provides corresponding index datasuch as the SSI which may include the SSI mean and SSI standarddeviation based on the activation map data for a given heart beat orinterval. As described herein, portions of the heart can be excludedfrom analysis based upon an identification of scar areas or other areasdetermined to have a negligible contribution to mechanical and/orelectrical function.

The index data 104 can be utilized to determine therapy parameters toachieve a desired therapeutic result for a given patient. For instance,the therapy parameters (e.g., location and stimulation parameters) canbe determined based upon an evaluation of the respective SSI indicescomputed for set of different therapy parameters. For example, thehighest SSI_(M), the lowest SSI_(SD) index or a combination ofrespective indices can be utilized to determine a desired lead locationand stimulation parameters.

FIGS. 5 and 6 will be utilized to illustrate the concept of histogramanalysis of activation time. For example, a histogram of activationtimes can be determined to quantify a percentage of the ventricle isfinishing after a set threshold (e.g., 1SD or 2SD) from the mean. Thehistogram analysis can be applied intraventricularly (within the rightor left ventricle) or interventricularly (between ventricles-over thewhole heart). Additionally, histogram analysis can be utilized to setone or more thresholds, such as thresholds for any of the indices shownand described herein. As described herein the thresholds can be utilizedto select patients as candidates for cardiac therapy.

FIG. 5 depicts an example of information determined from quantitativeanalysis of heart failure patients. FIG. 5 depicts a histogram 120 ofactivation time for left ventricles of a control population and ahistogram 122 of activation time for a set of patients. Plotted on eachhistogram are the mean and a first standard deviation (1SD) and a secondstandard deviation (2SD). By selecting a control population for thehistogram 120 from a normal or healthy group (e.g., patients with normalventricles, LVEF>50% and QRS duration <100 ms), statistical values forthe normal population can be determined, such as the MEAN+1SD orMEAN+2SD or another related value. The statistical value can be employedto define one or more thresholds. The histogram data for each of thepatients (from histogram 122) can be employed to evaluate theiractivation time relative to the threshold, such as shown in the table124 in FIG. 5. For instance, the table 126 shows the percentage ofactivation time for each patient's left ventricle that exceeds theMEAN+2SD determined from the control histogram 120. Also shown is theQRS duration for each of the patient's. Thus, the histogram analysis canprovide a further way to evaluate electrical dyssynchrony for eachpatient, which may be in addition to QRS duration or other existingcriteria.

As described herein, this evaluation can be performed to evaluate thecandidacy of each of the patients for cardiac therapy, such as includingCRT. There may be a percentage in the control histogram (e.g., athreshold) above which there a patient has little likelihood ofresponding to therapy. Accordingly, one or more thresholds can also bederived to help identify patient's that would be non-responders to suchcardiac therapy as to screen out patient that otherwise might appeargood candidates in view of other relevant factors.

FIGS. 6A and 6B depict examples of isochrone maps for different view ofthe heart, namely an anterior view, the left ventricular free wall andthe posterior view of a heart. The isochrone maps on the left side arefor a first patient (e.g., having a QRS duration of approximately 89 ms)and the maps on the right side of the figure are for a second patient(e.g., having a QRS duration of 108 ms). A physician thus can compare(e.g. in real-time or otherwise) activation maps as well as other dataherein to quantitatively analyze, for example, activation time for eachpatient as part of a patient screening or other evaluation of heartfunction.

FIG. 7 depicts another embodiment of a system 150 that can be utilizedfor assessing the function of a patient's heart 152, which has beeninserted within a patient's body, schematically depicted at 154. Thesystem 150 can perform the assessment of the heart 152 in real time aspart of a diagnostic or treatment procedure, such as to help a physiciandetermine parameters for delivering a therapy to the patient (e.g.,delivery location and amount and type of therapy). For example, acatheter, such as a pacing catheter, having one or more electrodes 156affixed thereto can be inserted into the body 154 as to contact thepatient's heart 152, endocardially or epicardially. Those skilled in theart will understand and appreciate various type and configurations ofpacing catheters and EP catheters that can be utilized to position theelectrode(s) 156 in the patient's body 154.

The therapy system 158 controls therapy delivered by the electrode(s)156. For instance, the therapy system 158 includes control circuitry 160that can communicate (e.g., supply) electrical signals via a conductivelink electrically connected between the electrodes 156 and the therapysystem 158. The control system 160 can control stimulation parameters(e.g., current, voltage, repetition rate, trigger delay, sensing triggeramplitude) for applying electrical stimulation via the electrode(s) 154to one or more location of the heart 152. The control circuitry 160 canset the stimulation parameters and apply stimulation based on automatic,manual (e.g., user input) or a combination of automatic and manual(e.g., semiautomatic controls. One or more sensors (not shown) can alsocommunicate sensor information to the therapy system 158, which islocated external to the patient's body 156. The position of theelectrodes 156 relative to the heart can be determined and tracked viaan imaging modality, a mapping system 162, direct vision or the like.The location of the electrodes and the therapy parameters thus can becombined to provide corresponding therapy parameter data.

Concurrently with providing a therapy via the therapy system 158,another system or subsystem can be utilized to acquire electrophysiologyinformation for the patient. In the example of FIG. 7, a sensor array164 includes one or more electrodes that can be utilized for recordingpatient activity. As one example, the sensor array 164 can correspond toan arrangement of body surface sensors that are distributed over aportion of the patient's torso for measuring electrical activityassociated with the patient's heart (e.g., as part of anelectrocardiographic mapping procedure). An example of a non-invasivesensor array that can be used is shown and described in Internationalapplication No. PCT/US2009/063803, which was filed 10 Nov. 2009, whichis incorporated herein by reference. Other arrangements of electrodescan be used, which may be a reduced set of electrodes that does notcover the entire torso and is designed for measuring electrical activityfor a particular purpose (e.g., to assist in delivery of therapy).

Alternatively or additionally, in other embodiments, the sensor array164 can be an invasive sensor, such as an EP catheter having a pluralityof electrodes. The EP catheter can be inserted into the patient's body154 and into the heart for mapping electrical activity for anendocardial surface such as the wall of a heart chamber. As anotheralternative, the sensor array 164 can be an arrangement of electrodesdisposed on other devices, such as patches, which can be placed on ornear a patient's heart, endocardially and/or epicardially. These patchescan be utilized during open chest and minimally invasive procedures torecord electrical activity.

In each of such example approaches for acquiring patient electricalinformation, including invasively, non-invasively, or a combination ofinvasive and non-invasive sensors, the sensor array(s) 164 provide thesensed electrical information to a corresponding measurement system 166.The measurement system 166 can include appropriate controls and signalprocessing circuitry 168 for providing corresponding measurement data170 that describes electrical activity detected by the sensors in thesensor array 164. The measurement data 170 can include analog or digitalinformation.

The control 168 can also be configured to control the data acquisitionprocess for measuring electrical activity and providing the measurementdata 170. The measurement data 170 can be acquired concurrently with thedelivering therapy by the therapy system, such as to detect electricalactivity of the heart 152 that occurs in response to applying a giventherapy (e.g., according to therapy parameters). For instance,appropriate time stamps can be utilized for indexing the temporalrelationship between the respective data 170 and therapy parameters tofacilitate the evaluation and analysis thereof. The control 168 can alsoimplement a defibrillation mode in which the electrodes are electricallydisconnected or otherwise reconfigured to provide a safe environment atwhich defibrillation can be performed to the patient's body 154 withouthaving to remove the electrodes from the sensor array 164.

Those skilled in the art will appreciate various other approaches thatcan be employed to obtain the patient measurement data 170. For example,the measurement data 166 can be acquired by myocardial activationimaging in which images of the myocardial activation sequence areobtained by combining measurements obtained by electrocardiographic bodysurface mapping with three-dimensional anatomical data.

The mapping system 162 is programmed to combine the measurement data 170corresponding to electrical activity of the heart 152 with patientgeometry data 172 by applying an appropriate algorithm to providecorresponding electroanatomical map data 174. The map data 174 can berepresent electrical activity of the heart 152, such as corresponding toa plurality of reconstructed electrograms distributed over a cardiacenvelope for the patient's heart (e.g., an endocardial or epicardialenvelope). As one example, the map data 174 can correspond toelectrograms for an epicardial surface of the patient's heart 152, suchas based on electrical data that is acquired non-invasively via sensorsdistributed on the body surface or invasively with sensors distributedon or near the epicardial envelope. Alternatively, the map data 174 canbe reconstructed for an endocardial surface of a patient's heart such asa portion of chambers of the patient's heart (e.g., left and rightventricles), such as based on electrical activity that is recordedinvasively using an EP catheter or similar devices or recordednon-invasively via body surface sensors. The map data can representelectrical activity for other cardiac envelopes. The particular methodsemployed by the mapping system 162 for reconstructing the electrogramdata can vary depending upon the approach utilized for acquiring themeasurement data 170.

In one example, the mapping system 162 generates the map data torepresent activation time computed for each of the plurality of pointson the surface of the heart from electrograms over a selected cardiacinterval (e.g., a selected beat). Since the measurement system 166 canmeasure electrical activity of the heart concurrently, the resultingelectrogram maps and activation maps (e.g., the map data 174) thus canalso represent concurrent data for the heart for analysis to quantify anindication of synchrony, as described herein. The interval for which theactivation times are computed can be selected based on user input.Additionally or alternatively, the selected intervals can besynchronized with the application of therapy by the therapy system 158.

In the example of FIG. 7, assuming a non-contact type of sensor array164, the mapping system 162 includes a map generator 176 that constructselectroanatomical map data by combining the measurement data 170 withpatient geometry data 172 through an inverse algorithm to reconstructthe electrical activity onto a representation (e.g., a three-dimensionalrepresentation) of the patient's organ. The mapping system 162 can alsoinclude an electrogram reconstruction engine 178 that processes theelectrical activity to produce corresponding electrogram data for eachof a plurality of identifiable points on the appropriate cardiacenvelope (e.g., an epicardial or endocardial surface) of the patient'sheart.

As an example, the geometry data 172 may be in the form of graphicalrepresentation of the patient's torso, such as image data acquired forthe patient. Such image processing can include extraction andsegmentation of anatomical features, including one or more organs andother structures, from a digital image set. Additionally, a location foreach of the electrodes in the sensor array 164 can be included in thepatient geometry data 172, such as by acquiring the image while theelectrodes are disposed on the patient and identifying the electrodelocations in a coordinate system through appropriate extraction andsegmentation. The resulting segmented image data can be converted into atwo-dimensional or three-dimensional graphical representation thatincludes the region of interest for the patient.

Alternatively, the geometry data 172 can correspond to a mathematicalmodel, such as can be a generic model or a model that has beenconstructed based on image data for the patient's organ. Appropriateanatomical or other landmarks, including locations for the electrodes inthe sensor array 164 can be identified in the geometry data 172 tofacilitate registration of the electrical measurement data 170 andperforming the inverse method thereon. The identification of suchlandmarks can be done manually (e.g., by a person via image editingsoftware) or automatically (e.g., via image processing techniques).

By way of further example, the patient geometry data 172 can be acquiredusing nearly any imaging modality based on which a correspondingrepresentation can be constructed, such as described herein. Suchimaging may be performed concurrently with recording the electricalactivity that is utilized to generate the patient measurement data 170or the imaging can be performed separately (e.g., before the measurementdata has been acquired).

The system 150 also includes an analysis method 180 that is programmedto assess heart function and provide heart function data 182 based onthe map data 174. As described herein, the heart function data 182 canbe in the form of an index or indices. Additionally, the analysis system180 can communicate with the therapy system 158 and the measurementsystem 166, such as to synchronize and control delivery of therapy andmeasurement of electrical activity via the sensor array 164. Theanalysis system 180 can compute a plurality of indices for differenttherapy parameters (e.g., location and electrical stimulationparameters) based on the map data 174. The analysis method 180 can alsocompute histogram information (e.g., as shown and described in FIG. 5).The analysis method 180 can also determine a desired (e.g., optimum) setof therapy parameters for achieving desired therapeutic results. Theanalysis system 180 can also provide an indication of a patient'scandidacy for a therapy, which may include one or both of an indicationof the patient's expected responsiveness to therapy or expectednon-responsiveness to therapy.

In the example, of FIG. 7, the analysis method 180 includes a selectionfunction 184, an exclusion function 186, a synchrony calculator 188 andan optimization component 190. The selection function 184 can beprogrammed to select an interval of a heart beat for which the analysisand heart function data will be calculated. The selection function 184can be automated, such as synchronized to application of the therapy viathe therapy system. Alternatively, the selection function 184 can bemanual or semiautomatic, such as described herein, for selecting one ormore cardiac interval.

The exclusion function 186 is programmed to identify and exclude areasfrom analysis, such as scar areas. The exclusion can be performed basedon electrical information, imaging data (e.g., from the patient geometrydata 172) or both. The exclusion function 186 can be automatic, based onevaluation of the electrical and/or imaging data, or it can be manual orsemiautomatic, such as described herein. Each area (if any) identifiedfor exclusion can be co-registered with the map data, such that theidentified areas are not utilized as part of the calculations forassessing heart function. Alternatively, the exclusion can be utilizedto remove results.

The synchrony calculator 188 can be programmed to compute one or moreindication of synchrony (e.g., in the form of an index) that provides anassessment of heart function as the heart function data. For instance,the synchrony calculator 188 can be programmed to perform one or more ofthe calculations (e.g., for computing GSI, SSI, ICI and/or lateactivation index) shown and described here to provide the heart functiondata 182 accordingly. the synchrony calculator can further compute oneor more quantitative indication of synchrony based on conduction data191, such as disclosed herein with respect to FIG. 2. The conductiondata 191 further can be utilized to identify a normal indication ofsynchrony for a given segment (e.g., anatomical region), such thatevaluation of the conduction data relative to the computed synchronydata for a given patient can be used to improve synchrony for the entireheart as well as independently for one or more respective segments thatmay be determined to be important for mechanical function (e.g., asindicated by a weighting function), as disclosed herein.

The optimization component 190 can be programmed to determine one ormore therapy delivery locations (e.g., one or more pacing sites). Thismay involve positioning one or more electrodes at test sites andevaluating the synchrony determined by the synchrony calculator 188. Theelectrodes can be implanted at locations based on this evaluation. Thiscan vary depending on, for example, the number and type of electrodesbeing implanted.

Additionally or alternatively, the optimization component 190 can beutilized to determine one or more therapy parameters, such aspost-implantation of the electrodes. The parameterization forprogramming the implanted device can be based on parameters determinedintraoperatively based on quantitative analysis computed by thesynchrony calculator 188. For instance, the optimization component 190can evaluate heart function data (e.g., provided as one or more index)182 that is computed by the synchrony calculator 188 from map data(e.g., activation map data) 174 acquired in response to therapy appliedto the heart during a calibration or programming mode for a plurality ofdifferent therapy parameters.

Those skilled in the art will understand appreciate various approachesthat can be utilized to vary the location and/or other therapyparameters to achieve a desired therapeutic result. The optimizationcomponent 190 can evaluate the therapeutic result, for example, byminimizing the index or indices computed by the index calculator foreach set of parameters. The type of location information and therapyparameters further can vary depending on the type of therapy device andthe number of electrodes. For example, the therapy system 158 can beimplemented to provide for single chamber pacing or multi-chamber pacingas well as may be implemented endocardially or epicardially with respectto the heart 152. As a further example, the optimization can be utilizedto adjust parameters for a standard lead configuration or adjust anelectric field vector for a lead configuration employing a plurality ofventricular leads.

The heart function data 182 can be utilized to present an indication ofheart function on a display 192, which can include text and/or graphics.For instance, the indication of heart function for each set ofparameters can be provided as a graphical element that is superimposedonto a cardiac map 194 being visualized on the corresponding display192. It is to be understood and appreciated that the determination ofthe heart function data 182 can be performed in real time such that therepresentation of the heart function on the cardiac map 194 can providereal time guidance and information to facilitate positioning theelectrodes 156 within the patient's body 154 as well as settingparameters for delivering therapy to the patient. The therapy parameterscan also be provided on the display 192.

By way of further example, the analysis system 180 can employ othermeasures, such as like percentage of LV that late activated (e.g., fromhistogram or other data). As an example, the synchrony calculator 188can be programmed to group the time-based electrical data (e.g.,activation or repolarization times for each of the plurality of pointsinto two or more temporally contiguous set of points. For example,points having electrical activity (e.g., a computed activation time orrepolarization time) within a corresponding first time period relativeto a predetermined time threshold (e.g., an activation time threshold)can be grouped into a first subset of points. Similarly, a temporallycontiguous set of points within a corresponding second time period cancorrespond to a second subset of the points. Thus, the first subset ofpoints can be those having a time before the threshold and the secondsubset can be those that occur after the threshold. The synchronycalculator 188 can compute an index of late activation based on arelative quantity of the plurality of points are determined to have anactivation time or repolarization time that occurs after the computedtime threshold (e.g., based on how many points in the second subsetversus the first subset). This late activation can be performedintraventricularly (e.g., within the left and/or right ventricles).

Additionally, the late activation can also be computed for each of aplurality of spatial segments into which the heart can be divided, suchas anatomical regions or other geometrical regions. For example, thepoints can be grouped into segments according to each segments relativecontribution to mechanical function of the heart. Relative segmentalweighting can be applied to such segments to evaluate relative synchronyamong the segments as they pertain to heart function. Additionally, theanalysis system 180 can further determine how percentage of activationof a chamber changes intraoperatively, such as in response to applyingdifferent types or therapies or different therapy (e.g., pacing) modes.

As a further example, the late activation time can be computed for aplurality of different conditions (e.g., without CRT, and with CRTapplied at different locations and with different parameters) to providecorresponding indications of synchrony. The computed late activationtime for each condition can be compared (e.g., manually or by theanalysis system 180 automatically) to help evaluate patientresponsiveness to CRT as well as to determine CRT parameters asdisclosed herein.

In addition to the dyssynchrony computations described above, theanalysis system 180 may be configured to assess synchrony according toone or more of the following other calculations:

-   -   a. QRS onset (or end of pacing spike) to beginning of        ventricular activation. For instance, the analysis system 180        can determine an earliest LV activation from the map data (e.g.,        on isochrones) and subtract the beginning of QRS.    -   b. LV activation time from beginning to end: latest LV        activation time−earliest LV activation time.    -   c. LV delay estimation: the analysis system 180 can estimate LV        delay for the entire LV free wall area by dividing LV free wall        into segments and then calculate the size. Then estimate area        size. As one example, area size=x % (example) of the total area.        And the time of the last area is Time to x % LV free wall        activation. This can be to any percentage of the LV.    -   d. Locate the % of LV region that has an activation time that        occurs some predetermined percentage greater than (e.g., >50%)        of QRS duration. For example, if a patient has a QRS width of        120 ms, the analysis system 180 can compute the percentage of        the ventricle that activates in the last 20 ms (e.g., how much        activation occurs later than the normal 100 ms). The time        threshold can be programmable and can be set in response to a        user input.    -   The analysis thus can employ thresholds (e.g., corresponding to        normal values of synchrony, plus two standard deviations) for        these and other quantitative indications of synchrony disclosed        herein to ascertain whether the results of such analysis        indicates dyssynchrony as well as the degree of such        dyssynchrony.

FIG. 8A through FIG. 14 depict examples of electrocardiographic mapsthat can be generated to represent quantitative analysis of synchronybased on systems and methods disclosed herein (e.g., the analysis system20 of FIG. 1 or analysis method 180 of FIG. 7, respectively).

FIGS. 8A and 8B depict examples of electrocardiographic maps 200 and202, including a left-anterior-oblique (LAO) view in FIG. 8A and alateral view in FIG. 8B. The maps 200 and 202 in FIGS. 8A and 8B,respectively, depict activation maps showing interventricuardyssynchrony for a baseline patient condition.

FIGS. 9A and 9B depict examples of electrocardiographic maps 204 and 206demonstrating a response to delivery of a therapy (e.g., CRT) for thesame patient as in FIGS. 8A and 8B. A comparison between the maps 200and 202 relative to the maps 204 and 206 demonstrates a significantimprovement in response to delivery of the therapy. Thus, thecomparative analysis can confirm that the patient is a responder to CRT.

FIGS. 10A and 10B depict examples of electrocardiographic maps 208 and210 demonstrating a baseline condition for another patient. In the maps208 and 210, interventricular dyssynchrony is apparent as evidenced bythe much later activation time in the left ventricle than the rightventricle. FIGS. 11A and 11B depict examples of electrocardiographicmaps 212 and 214 demonstrating a patient response to delivery of atherapy for the same patient as in the example of FIGS. 10A and 10B. Inthe maps 212 and 214, the pacing results in increased late activationrelative to the baseline maps 208 and 210 of FIGS. 10A and 10B. In thisexample, the increased late activation in the left ventricle can beutilized to confirm that the patient is a non-responder to theparticular CRT. This can be used to select an alternative form ortherapy or surgery.

FIGS. 12, 13 and 14 depict examples of electrocardiographic maps 216,218 and 220 demonstrating responses for a given patient to delivery oftherapy, such as at different locations and with different therapyparameters (e.g., similar to the map 194 that can be output in theexample of FIG. 7). These maps 216, 218 and 220 or similar maps to helpdetermine lead placement and optimal pacing parameters, which can beutilized as tools during CRT and/or after CRT device implant.

In FIG. 12, the map 216 depicts an example of pacing in which one offour available leads (e.g., lead 217) is activated to supply an electricfield for providing CRT. In FIG. 13, the map 218 depicts an example ofbi-ventricular pacing in which a pair of leads (e.g., leads 219) areactivated to supply an electric field for providing CRT. While the map218 demonstrates an improved response relative to the example of FIG.12, there remains a late activation region in postero-lateral LV causingpoor electrical synchrony and a corresponding poor hemodynamic responseto such pacing. FIG. 14 depicts an example map 220 in which fouravailable leads (e.g., leads 221) is activated to provide pacing forCRT. The map 220 demonstrates significantly improved electricalsynchrony relative to the approaches in FIGS. 12 and 13 as to supportgood hemodynamic response to such pacing.

FIG. 15 is flow diagram depicting an example of a method 230 that can beutilized to facilitate lead placement for delivery of a therapy basedupon one or more quantified indication of synchrony, such as shown anddescribed herein. The method 230 can be implemented in the context ofthe system of FIG. 7, for example, as computer executable instructionscorresponding to the analysis method 180 of FIG. 7.

The method begins at 232 in which areas are identified and excluded fromfurther assessment in the method of 230. The areas can be identified ascorresponding to scar areas or areas otherwise having conduction or lowvoltage electrograms that are below a corresponding threshold. Theidentification can be performed automatically (e.g., via thresholding)or based on user selection of areas such as can be performed based onanalysis of imaging data such as described herein.

At 234, pacing parameters are set. The parameters can include a varietyof electrical stimulation parameters, which further can vary dependingon the number of electrodes. Examples of parameters that can be utilizedin the systems and methods disclosed herein include, current, voltage,repetition rate, trigger delay and sensing trigger amplitude. Theparameters can also include a delay between pacing times for differentelectrodes, such as an atrio-ventricular delay (e.g., for leads inatrium and ventricle) as well as ventricular-ventricular delays (e.g.,for leads in the respective ventricles). Parameters can also be set toestablish an electrical field vector by controlling stimulationparameters for different electrodes.

At 236, a therapy can be delivered at a location based on the initialparameters at 234. The therapy can include electrical stimulation, butis not limited to electrical stimulation. For instance, the therapy caninclude electrical pacing stimulation that is applied via a pacingelectrode or electrodes that have been inserted and are in contact withone or more corresponding locations of the heart. The location of theelectrodes can be determined from electrical information obtained by themapping system (system 162 of FIG. 7), based on imaging data (storedwith the patient geometry data 172 of FIG. 6), such as via x-ray (e.g.,chest -xray or fluoroscopy), ultrasound or other known imagingmodalities that can be performed in conjunction with pacing.

At 238, one or more indication of synchrony can be calculated and storedin memory as synchrony data. The synchrony data can include any one ormore of the indices disclosed herein, for example. At 240, adetermination is made as to whether additional pacing locations existfor which indices can be calculated as part of the method 230. Differentpacing parameters can also be adjusted for each location, if desired,such as can be implemented according to the method of FIG. 16 as aninner loop within the method 230 between 238 and 240. If one or moreadditional locations exist for discovering lead placement, the methodproceeds to 242 in which the location is changed accordingly. Eachlocation can be entered manually by the user or it can be determined byanalysis performed by the mapping system (e.g., mapping system 162 ofFIG. 7).

From 242, the method returns to 236 in which a corresponding therapy isapplied at the next location. In conjunction with application of thetherapy, an interval can be selected associated with the therapy that isbeing applied and corresponding time-based electrical characteristicscan be calculated as shown and described herein. Based upon thecalculated time-based electrical characteristics, at 238, thecorresponding index can be calculated and stored in memory.

Once the potential set of pacing locations have been exhausted or thetesting is otherwise terminated, the method proceeds to 244 in which thesynchrony data for each location can be evaluated. Based on theevaluation of synchrony data (e.g., a minimization thereof), a desiredlocation for delivery of therapy (e.g., lead placement) can bedetermined at 246. It will be understood and appreciated that theevaluation at 244 can be performed within the loop from 236 through 242,alternatively. Additionally, the results of the index calculations canbe utilized to help guide adjustments at 242 to facilitate determiningone or more appropriate locations that can be utilized for deliveringthe desired therapy.

FIG. 16 is flow diagram depicting an example of a method 250 that can beutilized for optimizing delivery of a therapy based upon a calculatingan index, such as shown and described herein. The method 250 can beimplemented in the context of the system 150 of FIG. 7, for example, ascomputer executable instructions corresponding to the analysis method180 of FIG. 7.

The method begins at 252 in which areas are identified and excluded fromfurther assessment in the method of 250. The areas can be identified ascorresponding to scar areas or areas otherwise having conduction or lowvoltage electrograms that are below a corresponding threshold. Theidentification can be performed automatically (e.g., via thresholding)or based on user selection of areas such as can be performed based onanalysis of imaging data such as described herein. A correspondinginterval of a beat can also be selected. The interval selection canoccur in response to a user input or automatically based upon evaluationof acquired electrical data that has been acquired in real time, asdisclosed herein.

At 254, initial therapy parameters can be set. As described herein, theparameters can include electrical stimulation parameters, such asamplitude, phase, duration and a relative delay between activation atdifferent lead locations. The parameters can also include locations forone or more leads at which stimulation is applied. At 256, a therapy canbe delivered at a location based on the initial parameters at 254. Thetherapy can include an electrical stimulation, but is not limited toelectrical stimulation. For instance, the therapy can include electricalpacing stimulation that is applied via a pacing electrode or electrodesthat have been inserted and are in contact with one or morecorresponding locations of the heart. The location of the electrodes canbe determined from electrical information obtained by the mapping system(system 162 of FIG. 7), based on imaging data (stored with the patientgeometry data 172 of FIG. 7), such as via x-ray (e.g., chest -xray orfluoroscopy), ultrasound or other known imaging modalities that can beperformed in conjunction with pacing.

At 258, one or more index can be calculated and stored in memory. Theindex can include any one or more of the indices disclosed herein. At260, a determination is made as to whether any additional parametersexist for which indices can be calculated as part of the method 250. Asmentioned above, the parameters can include location, amplitude, phase,frequency or the like. The particular parameters for a given pacingelectrode structure can vary according to the particular pacingelectrode or combination of electrodes that are being utilized forimplementing such pacing. If additional parameters exists for whichindices are to be calculated, the method proceeds to 262 in whichparameter adjustments are made. The parameter adjustments at 260 caninclude moving to a different location, changing an electrodestimulation parameter or a combination thereof. The adjustments can beautomated in response to a control signal or manual based on informationthat can be presented to the user.

From 262, the method returns to 256 in which a corresponding therapy isapplied at the location for the next therapy parameters. In conjunctionwith application of the therapy, an interval is selected associated withthe therapy that is being applied and corresponding activation data canbe calculated as shown and described herein. Based upon the calculatedactivation data, at 258, the corresponding index can be calculated andstored in memory.

Once available set of parameters have been exhausted or the testing isotherwise terminated, the method proceeds to 264 in which the index datacan be evaluated to determine a desired set of parameters. Based on theevaluation of index data (e.g., a minimization thereof), a set oftherapy parameters can be determined at 266. It will be understood andappreciated that the evaluation at 264 can be performed within the loopfrom 254 through 262, alternatively. Additionally, the results of theindex calculations can be utilized to help guide stimulation parameteradjustments at 260 to facilitate determining an appropriate set ofparameters that can be utilized for delivering the desired therapy.

In view of the foregoing structural and functional description, thoseskilled in the art will appreciate that portions of the invention may beembodied as a method, data processing system, or computer programproduct. Accordingly, these portions of the present invention may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, or an embodiment combining software and hardware, such asshown and described with respect to the computer system of FIG. 17.Furthermore, portions of the invention may be a computer program producton a computer-usable storage medium having computer readable programcode on the medium. Any suitable computer-readable medium may beutilized including, but not limited to, static and dynamic storagedevices, hard disks, optical storage devices, and magnetic storagedevices.

Certain embodiments of the invention have also been described hereinwith reference to block illustrations of methods, systems, and computerprogram products. It will be understood that blocks of theillustrations, and combinations of blocks in the illustrations, can beimplemented by computer-executable instructions. Thesecomputer-executable instructions may be provided to one or moreprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus (or a combination ofdevices and circuits) to produce a machine, such that the instructions,which execute via the processor, implement the functions specified inthe block or blocks.

These computer-executable instructions may also be stored incomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory result in an article of manufacture including instructions whichimplement the function specified in the flowchart block or blocks. Thecomputer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

In this regard, FIG. 17 illustrates one example of a computer system 300that can be employed to execute one or more embodiments of theinvention, such as including acquisition and processing of sensor data,processing of image data, as well as analysis of transformed sensor dataand image data associated with the analysis of cardiac electricalactivity. Computer system 300 can be implemented on one or more generalpurpose networked computer systems, embedded computer systems, routers,switches, server devices, client devices, various intermediatedevices/nodes or stand alone computer systems. Additionally, computersystem 300 can be implemented on various mobile clients such as, forexample, a personal digital assistant (PDA), laptop computer, pager, andthe like, provided it includes sufficient processing capabilities toperform the functions disclosed herein.

Computer system 300 includes processing unit 301, system memory 302, andsystem bus 303 that couples various system components, including thesystem memory, to processing unit 301. Dual microprocessors and othermulti-processor architectures also can be used as processing unit 301.System bus 303 may be any of several types of bus structure including amemory bus or memory controller, a peripheral bus, and a local bus usingany of a variety of bus architectures. System memory 302 includes readonly memory (ROM) 304 and random access memory (RAM) 305. A basicinput/output system (BIOS) 306 can reside in ROM 304 containing thebasic routines that help to transfer information among elements withincomputer system 300.

Computer system 300 can include a hard disk drive 307, magnetic diskdrive 308, e.g., to read from or write to removable disk 309, and anoptical disk drive 310, e.g., for reading CD-ROM disk 311 or to readfrom or write to other optical media. Hard disk drive 307, magnetic diskdrive 308, and optical disk drive 310 are connected to system bus 303 bya hard disk drive interface 312, a magnetic disk drive interface 313,and an optical drive interface 314, respectively. The drives and theirassociated computer-readable media provide nonvolatile storage of data,data structures, and computer-executable instructions for computersystem 300. Although the description of computer-readable media aboverefers to a hard disk, a removable magnetic disk and a CD, other typesof media that are readable by a computer, such as magnetic cassettes,flash memory cards, digital video disks and the like, in a variety offorms, may also be used in the operating environment; further, any suchmedia may contain computer-executable instructions for implementing oneor more parts of the present invention.

A number of program modules may be stored in drives and RAM 305,including operating system 315, one or more application programs 316,other program modules 317, and program data 318. The applicationprograms and program data can include functions and methods programmedto acquire, process and display electrical data from one or moresensors, such as shown and described herein. The application programsand program data can include functions and methods programmed to processdata acquired for a patient for assessing heart function and/or fordetermining parameters for delivering a therapy, such as shown anddescribed herein with respect to FIGS. 1-16.

A user may enter commands and information into computer system 300through one or more input devices 320, such as a pointing device (e.g.,a mouse, touch screen), keyboard, microphone, joystick, game pad,scanner, and the like. For instance, the user can employ input device320 to edit or modify a domain model. These and other input devices 320are often connected to processing unit 301 through a corresponding portinterface 322 that is coupled to the system bus, but may be connected byother interfaces, such as a parallel port, serial port, or universalserial bus (USB). One or more output devices 324 (e.g., display, amonitor, printer, projector, or other type of displaying device) is alsoconnected to system bus 303 via interface 326, such as a video adapter.

Computer system 300 may operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer328. Remote computer 328 may be a workstation, computer system, router,peer device, or other common network node, and typically includes manyor all the elements described relative to computer system 300. Thelogical connections, schematically indicated at 330, can include a localarea network (LAN) and a wide area network (WAN).

When used in a LAN networking environment, computer system 300 can beconnected to the local network through a network interface or adapter332. When used in a WAN networking environment, computer system 300 caninclude a modem, or can be connected to a communications server on theLAN. The modem, which may be internal or external, can be connected tosystem bus 303 via an appropriate port interface. In a networkedenvironment, application programs 316 or program data 318 depictedrelative to computer system 300, or portions thereof, may be stored in aremote memory storage device 340.

What have been described above are examples and embodiments of theinvention. It is, of course, not possible to describe every conceivablecombination of components or methodologies for purposes of describingthe invention, but one of ordinary skill in the art will recognize thatmany further combinations and permutations of the present invention arepossible. Accordingly, the invention is intended to embrace all suchalterations, modifications and variations that fall within the scope ofthe appended claims. In the claims, unless otherwise indicated, thearticle “a” is to refer to “one or more than one.”

1. A method for assessing a function of a patient's heart, comprising:determining a time-based electrical characteristic for a plurality ofpoints corresponding to at least one spatial region of the heart;grouping the plurality of points into at least two subsets of pointsbased on at least one of a spatial location for each of the plurality ofpoints or the time-based electrical characteristic for each of theplurality of points; and quantifying an indication of synchrony for theheart based on relative analysis of the determined time-based electricalcharacteristic for each of the at least two subsets of points.
 2. Themethod of claim 1, wherein the at least two subsets of points correspondto different chambers of the heart, the method further comprisingcomputing an index having at least one value representing synchronybetween the different chambers.
 3. The method of claim 2, wherein thedifferent chambers of the heart comprise the left ventricle and theright ventricle.
 4. The method of claim 2, wherein the quantifyingfurther comprises: computing a first statistical parameter for each ofthe plurality of points associated with a first chamber of the heart,computing a second statistical parameter for each of the plurality ofpoints associated with a second chamber of the heart; computing adifference between the first statistical parameter and the secondstatistical parameter to provide the index.
 5. The method of claim 1,wherein the at least two subsets of points correspond to a plurality ofdifferent spatial segments within each of left and right portions of theheart, the method further comprising: quantifying an assessment of thesynchrony for each of the plurality of segments in the left portion ofthe heart based on the time-based electrical characteristic determinedfor the plurality of points in each respective segment thereof; andquantifying an assessment of the synchrony for each of the plurality ofsegments in the right ventricle based on the time-based electricalcharacteristic determined for the plurality of points in each respectivesegment thereof.
 6. The method of claim 5, further comprising weightingeach of the assessments for each of the plurality of segments to providea weighted segmental assessment of synchrony that accounts for acontribution of each segment to a mechanical function of the heart. 7.The method of claim 1, wherein the time-based electrical characteristicis determined for each of the plurality of points based on electricalmeasurements acquired concurrently during a same heart beat.
 8. Themethod of claim 7, wherein the electrical measurements are derived froma non-invasive arrangement of sensors attached to the patient.
 9. Themethod of claim 1, wherein the time-based electrical characteristiccomprises at least one of an activation time or a repolarization timecomputed for each of the plurality of points.
 10. The method of claim 1,further comprising: identifying an area of the heart that does notcontribute to mechanical function; and excluding the identified areafrom the at least one spatial region of the heart such that pointscorresponding to the excluded area are not used for quantifying theindication of synchrony.
 11. The method of claim 10, wherein the area ofthe heart are identified based on imaging data or an analysis ofelectrical properties thereof.
 12. The method of claim 11, wherein theelectrical properties are determined from the electrical characteristicacquired for each of a plurality of points on the at least one spatialregion of the heart.
 13. The method of claim 1, further comprising usingthe indication of synchrony to determine at least one of a delivery sitefor a therapy or a parameter for delivery of a therapy to the heart. 14.The method of claim 13, wherein the therapy is cardiac resynchronizationtherapy.
 15. The method of claim 13, further comprising measuringelectrical signals corresponding to operation of the heart in responseto delivery of the therapy, the time-based electrical characteristic foreach of the plurality of points being determined from the measuredelectrical signals.
 16. The method of claim 13, further comprisingcomputing an indication of synchrony in response to therapy delivered ateach of a plurality of locations and evaluating each indication ofsynchrony to determine which location to establish as a site fordelivering the therapy.
 17. The method of claim 2, further comprisingdetermining an indication of a patient's candidacy for a therapy basedon the indication of synchrony.
 18. The method of claims 1, furthercomprising: computing histogram data for a plurality of segments of theheart, respective subsets of the plurality of points residing in each ofthe plurality of segments of the heart; and computing an index thatquantifies the indication of synchrony based on the histogram datacorresponding to one or more different segments of a patient's heart.19. The method of claim 1, further comprising: identifying one of the atleast two subsets of points according to which points are determined tohave an activation time that occurs after a predetermined threshold; andcomputing the indication of synchrony as an index of late activationbased on a relative quantity of the plurality of points having anactivation time that occurs after the predetermined threshold.
 20. Themethod of claim 1, further comprising further comprising generating anoutput that displays a graphical representation of the indication ofsynchrony on a graphical depiction of a heart.
 21. A system comprising:memory to store data and machine-executable instructions, the dataincluding electrical data representing electrical signals for aplurality of points spatially distributed across a cardiac envelope; aprocessor to access the memory and execute the instructions, which whenexecuted cause the processor to: quantify an indication of synchrony fora patient's heart based on analysis of a first set of the electricaldata associated with a first subset of the plurality of points relativeto a second set of set of the electrical data associated with a secondsubset of the plurality of points.
 22. The system of claim 21, whereinthe first subset of the plurality of points define a spatiallycontiguous set of points in a corresponding first spatial region of thecardiac envelope and the second subset of the plurality of points definea spatially contiguous set of points in a corresponding second spatialregion of the cardiac envelope.
 23. The system of claim 22, wherein eachof the first and second spatial regions correspond to the left and rightventricles of the heart, respectively, the instructions, when executing,further causing the processor to compute an index having at least onevalue representing synchrony between the left and the right ventricles.24. The system of claim 22, wherein first spatial region comprises afirst chamber of the heart and the second spatial region comprises asecond chamber of the heart, the instructions, when executed, furthercausing the processor to: compute a first statistical parameter as afunction of at least one of an activation time or repolarization timefor each of the plurality of points associated with the first chamber ofthe heart; compute a second statistical parameter as a function of atleast one of an activation time or repolarization time for each of theplurality of points associated with the second chamber of the heart; andcompute a difference between the first statistical parameter and thesecond statistical parameter to provide a corresponding index.
 25. Thesystem of claim 22, wherein the first spatial region comprises aplurality of segments within a left chamber of the heart and the secondspatial region comprises a plurality of segments within a right chamberof the heart, the instructions, when executed, further causing theprocessor to: quantify an assessment of the synchrony for each of theplurality of segments in the left portion of the heart based on at leastone of an activation time or repolarization time determined for theplurality of points in each respective segment thereof the left chamber;and quantify an assessment of the synchrony for each of the plurality ofsegments in the right chamber based on at least one of an activationtime or repolarization time determined for the plurality of points ineach respective segment thereof the right chamber.
 26. The system ofclaim 25, wherein the assessment for each of the plurality of segmentsis weighted according to an expected contribution of each respectivesegment to a mechanical function of the heart such that each assessmentcorresponds to a weighted segmental assessment of synchrony thataccounts for mechanical function of the heart.
 27. The system of claim21, further comprising an arrangement of sensors configured to measureelectrical activity for the patient's heart concurrently during a sameheart beat, the electrical data being derived from the measuredelectrical activity.
 28. The system of claim 21, the instructions, whenexecuted, further causing the processor to identify an area of the heartthat does not contribute to mechanical function; and excluding each ofthe plurality of points that reside in the identified area such that theexcluded points are not used in quantifying the indication of synchrony.29. The system of claim 28, wherein the area of the heart is identifiedbased on imaging data for the heart or based on an analysis ofelectrical properties thereof determined from the electrical data. 30.The system of claim 21, further comprising a therapy device configuredto deliver a therapy to the patient's heart, the instructions, whenexecuted, further causing the processor to provide an outputrepresenting the indication of synchrony in response to delivery of thetherapy by the therapy device.
 31. The system of claim 21, theinstructions, when executed, further causing the processor to: computehistogram data for a plurality of segments of the heart; and compute anindex corresponding to the indication of synchrony based on thehistogram data corresponding to one or more different segments of apatient's heart.
 32. The system of claim 21, wherein the first subset ofthe plurality of points correspond to a temporally contiguous set ofpoints within a corresponding first time period relative to a timethreshold and the second subset of the plurality of points correspond toa temporally contiguous set of points within a corresponding second timeperiod relative to the time threshold, the second time period beingnon-overlapping with the first time period.
 33. The system of claim 32,the instructions, when executed, further causing the processor to:identify one of the at least two subsets of the plurality of pointsaccording to which points are determined to have an activation time orrepolarization time that occurs after a computed time threshold; andcompute an index of late activation or repolarization based on arelative quantity of the plurality of points determined to have anactivation time or repolarization time that occurs after the computedtime threshold.
 34. The system of claim 33, the instructions, whenexecuted, further causing the processor to: group plurality of pointsinto a plurality of different spatial segments for at least one of leftand right ventricles of the heart; compute a statistical indication ofthe activation time or repolarization time for each of the plurality ofdifferent spatial segments; compute the index of late activation orrepolarization for each of the plurality of different spatial segmentsbased on the respective statistical indication of the activation time orrepolarization time thereof.
 35. The system of claim 21, theinstructions, when executed, further causing the processor to generatean output that displays a graphical representation of the indication ofsynchrony on a graphical depiction of a heart.